HCIL-2009-13

Designing graph drawings that effectively communicate the underlying
network is challenging as for every network there are many
potential unintelligible or even misleading drawings. Automated
graph layout algorithms have helped, but frequently generate ineffective
drawings. In order to build awareness of effective graph
drawing strategies, we detail readability metrics on a [0,1] continuous
scale for node occlusion, edge crossing, edge crossing angle,
and edge tunneling and summarize many more. Additionally, we
define new node & edge readability metrics to provide more localized
identification of where improvement is needed. These are
implemented in SocialAction, a tool for social network analysis, in
order to direct users towards poor areas of the drawing and provide
real-time readability metric feedback as users manipulate it. These
contributions are aimed at heightening the awareness of network
analysts that the images they share or publish could be of higher
quality, so that readers could extract relevant information.